Humans acquire knowledge and develop cognitive abilities through active engagement with their surroundings. In the educational context, learning is enhanced when individuals interact dynamically with knowledge systems and receive personalized feedback. In the era of artificial intelligence, Artificial Intelligence Generated Content (AIGC) technology offers new ways to transform traditional learning processes, fostering adaptability, creativity, and engagement. This study aims to explore the influence of AIGC on K12 cross-disciplinary STEAM education, considering its role in multi-disciplinary integration, dynamic learning path generation, and the evaluation of AI-enhanced learning outcomes. This study consists of three major phases. Phase One involves a qualitative literature review to define key research questions, analyzing topics such as “AI-Powered Knowledge Adaptation,” “Personalized Learning Pathways,” “Multi-Disciplinary Content Synthesis,” and “Collaborative Learning Enhancement.” Phase Two comprises experimental studies in a STEAM learning environment, incorporating structured focus group discussions, the deployment of AIGC tools, and assessments of learning engagement. Phase Three focuses on evaluating results through statistical analysis, examining student performance improvements, collaboration effectiveness, and motivational changes. Experimental results reveal that the AIGC-powered STEAM education model significantly improves students’ problem-solving skills (32% increase), teamwork efficiency (29% increase), and learning motivation (35% increase). The findings of this research provide theoretical and practical evidence supporting the integration of AIGC in K12 education. They also highlight the potential for AI-driven personalized learning to reshape educational frameworks, making them more adaptive, student-centered, and interdisciplinary [1].